Answer M1: tract loads both face graphs once their dims are pinned

Neither InsightFace export parses as shipped -- SCRFD fails at its input
node, ArcFace at the first Conv -- which is the same wall dr-segment hit
on YOLO's dynamic export. Both load cleanly with the input dims frozen,
so the pure-Rust runtime holds for the face pipeline too.

tools/fix-face-model-shapes.sh does the freezing, and exists so the
artefact is reproducible rather than a binary someone once produced. It
takes two forms because the two graphs need different ones: ArcFace's
batch is a named dim_param, SCRFD's H and W are dynamic but unnamed.

Also notes YuNet loading with no intervention, which matters for the
licence question in faces.md 2.3.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>

core/dr-face/src/detect.rs

@@ -0,0 +1,87 @@
+//! SCRFD face detection (docs/faces.md §4).
+//!
+//! For now: enough of the loader to answer M1 — whether tract will parse these
+//! graphs at all — plus the load-time shape validation that keeps a YuNet file
+//! from being decoded as an SCRFD one.
+
+use crate::{install_backend, FaceError};
+
+/// A loaded SCRFD graph.
+pub struct Detector {
+    session: ort::session::Session,
+    /// Feature-map count: 3 for strides {8,16,32}, 4 for {8,16,32,64}.
+    ///
+    /// Discovered from the output count rather than assumed, because both
+    /// exports exist and hardcoding 3 silently ignores the largest faces in a
+    /// four-stride model.
+    strides: usize,
+}
+
+/// Strides, in the order SCRFD emits them.
+pub const ALL_STRIDES: [usize; 4] = [8, 16, 32, 64];
+
+/// Anchors per feature-map location.
+pub const ANCHORS: usize = 2;
+
+impl Detector {
+    pub fn from_path(path: impl AsRef<std::path::Path>) -> Result<Self, FaceError> {
+        let bytes = std::fs::read(path).map_err(FaceError::ModelRead)?;
+        Self::from_bytes(&bytes)
+    }
+
+    pub fn from_bytes(bytes: &[u8]) -> Result<Self, FaceError> {
+        install_backend();
+
+        let session = ort::session::Session::builder()
+            .map_err(FaceError::Inference)?
+            .commit_from_memory(bytes)
+            .map_err(FaceError::Inference)?;
+
+        let n_out = session.outputs().len();
+        if n_out % 3 != 0 || !(9..=12).contains(&n_out) {
+            return Err(FaceError::WrongModel {
+                expected: "InsightFace SCRFD",
+                detail: format!("expected 9 or 12 outputs, got {n_out}"),
+            });
+        }
+        let strides = n_out / 3;
+
+        // The check that actually distinguishes the models: score, box and
+        // landmark groups end in 1, 4 and 10 respectively. YuNet also has
+        // twelve outputs, so the count alone proves nothing.
+        for (group, expected_last) in [1_i64, 4, 10].into_iter().enumerate() {
+            for s in 0..strides {
+                let idx = group * strides + s;
+                let out = &session.outputs()[idx];
+                let last: Option<i64> =
+                    out.dtype().tensor_shape().and_then(|d| d.last().copied());
+                if last != Some(expected_last) {
+                    return Err(FaceError::WrongModel {
+                        expected: "InsightFace SCRFD",
+                        detail: format!(
+                            "output '{}' last dim is {:?}, expected {expected_last}",
+                            out.name(), last
+                        ),
+                    });
+                }
+            }
+        }
+
+        Ok(Self { session, strides })
+    }
+
+    /// Number of stride levels this graph emits.
+    pub fn strides(&self) -> &'static [usize] {
+        &ALL_STRIDES[..self.strides]
+    }
+
+    /// The graph's declared input shape, for diagnosing a dynamic export.
+    pub fn input_shape(&self) -> Option<Vec<i64>> {
+        self.session
+            .inputs()
+            .first()?
+            .dtype()
+            .tensor_shape()
+            .map(|s| s.to_vec())
+    }
+}